1. Field
One or more embodiments of the following description relate at least to an apparatus, method, and medium detecting an object pose.
2. Description of the Related Art
Since humans use both of their eyes in their daily lives, they may recognize human body poses quite well at short and long distances, e.g., even with low resolution or limited information. However, in a computational vision system, it is difficult to recognize different human body poses, though such recognitions may be desired in various fields.
To solve such a problem, a conventional model-based approach has been generally used to solely recognize different poses. The conventional model-based approach fits a human body model to an input image by measuring the similarity between the overlap of a human body model and an associated image region. However, it is difficult to apply the conventional model-based approach to distinguish between complex poses, such as sitting or lying down poses where different body parts have overlapping depths, thereby generating a large number of occlusions of respective overlapped body parts, such as in the movements of the body parts when practicing yoga or stretching, where it is common for different body parts to overlap when viewed from a particular view point. Additionally, since the conventional model-based approach typically requires high computational capabilities, it is difficult to apply the conventional model-based approach to an embedded environment, e.g., a computational system designed for specific control functions within a larger system or complete device often including hardware and potentially mechanical parts. The tracking of body parts or poses is similarly difficult when there are quick movements that require such high computational capabilities. In addition, the conventional model-based approach is not robust against segmentation errors, e.g., errors in the determined extent, periphery, or contour, as only examples, of a portion of an image that is set to be segmented or separately identified compared to a remainder of the image.